Zhang Junbo, Chen Zhuohui, Peng Yanyi, Zhang Lingyue, Xiao Bo, Zhang Mengqi
Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, China.
Biochem Biophys Res Commun. 2025 Oct 10;784:152659. doi: 10.1016/j.bbrc.2025.152659. Epub 2025 Sep 15.
Ischemic stroke (IS) accounts for 71 % of all strokes, whose diagnosis and prognosis require further exploration. Neutrophil extracellular traps (NETs) are produced by neutrophils, and there is already evidence that NETs play a role in IS, but further studies about crosstalk between immune cells, pathways and NETs are still needed.
To assess the expression of neutrophil extracellular traps (NETs), we utilized single sample Gene Set Enrichment Analysis. Stroke-associated NETs genes (SN genes) were identified through differential expression analysis combined with Weighted Correlation Network Analysis. Based on these SN genes, we developed a sophisticated diagnostic model incorporating machine learning techniques. Furthermore, we constructed a single-cell atlas of neutrophil transitions in post-stroke mice. Validation of our findings was conducted both in vitro and in vivo. In vitro, we employed oxygen-glucose deprivation (OGD) experiments to simulate ischemic conditions, facilitating the assessment of NETs formation and monitoring alterations in SN genes expression within neutrophils. In vivo, validation involved tracking changes in peripheral blood levels of these genes in a mouse model of transient middle cerebral artery occlusion (tMCAO) post-cerebral ischemia.
A detailed single-cell landscape depicting the dynamic transitions of neutrophils within the cerebral microenvironment post-stroke has been elaborately constructed. NETs displayed significant differential expression between IS and control groups in peripheral blood, correlating strongly with the activities of neutrophils and macrophages. Pathways pertinent to IS and NETs were delineated. A diagnostic model incorporating two SN genes was developed, demonstrating an AUC greater than 0.98, effectively pinpointing the hyperacute phase of IS. Additionally, the ceRNA networks concerning IS and NETs were mapped out. In vitro validation with oxygen-glucose deprivation (OGD) experiments revealed marked changes in NET formation and SN genes expression in neutrophils, corroborating our computational predictions. In vivo validation using a mouse transient middle cerebral artery occlusion (tMCAO) model confirmed significant changes in peripheral blood levels of F12 and PLXDC2 after cerebral ischemia, proving the excellent predictive value of these markers for IS.
This study elucidates the complex roles and dynamic changes of neutrophils within the cerebral microenvironment of mice from 3 h to 3 days following stroke onset. We have identified key genes, immune cells, signaling pathways, and ceRNA networks implicated in the formation of NETs in IS. Our study constructed a robust diagnostic model capable of detecting the hyperacute phase of IS, with an AUC value greater than 0.98. The inclusion of experimental validation for the SN genes F12 and PLXDC2 not only corroborates our model's predictive accuracy but also underscores its potential utility in clinical settings. These findings offer promising avenues for improving early diagnosis and potentially guiding therapeutic strategies in IS.
缺血性中风（IS）占所有中风的71%，其诊断和预后仍需进一步探索。中性粒细胞胞外诱捕网（NETs）由中性粒细胞产生，已有证据表明NETs在IS中发挥作用，但仍需要对免疫细胞、信号通路与NETs之间的相互作用进行进一步研究。
为评估中性粒细胞胞外诱捕网（NETs）的表达，我们采用了单样本基因集富集分析。通过差异表达分析结合加权相关网络分析，鉴定出与中风相关的NETs基因（SN基因）。基于这些SN基因，我们开发了一个结合机器学习技术的精密诊断模型。此外，我们构建了中风后小鼠中性粒细胞转变的单细胞图谱。我们在体外和体内对研究结果进行了验证。在体外，我们采用氧糖剥夺（OGD）实验模拟缺血条件，以评估NETs的形成，并监测中性粒细胞内SN基因表达的变化。在体内，验证包括在小鼠大脑中动脉短暂闭塞（tMCAO）脑缺血模型中追踪这些基因外周血水平的变化。
精心构建了一个详细的单细胞图谱，描绘了中风后大脑微环境中中性粒细胞的动态转变。NETs在缺血性中风组和对照组的外周血中表现出显著的差异表达，与中性粒细胞和巨噬细胞的活性密切相关。明确了与缺血性中风和NETs相关的信号通路。开发了一个包含两个SN基因的诊断模型，其曲线下面积（AUC）大于0.98，能有效确定缺血性中风的超急性期。此外，还绘制了与缺血性中风和NETs相关的竞争性内源性RNA（ceRNA）网络。氧糖剥夺（OGD）实验的体外验证显示中性粒细胞中NETs形成和SN基因表达有明显变化，证实了我们的计算预测。使用小鼠大脑中动脉短暂闭塞（tMCAO）模型的体内验证证实，脑缺血后外周血中F12和PLXDC2水平有显著变化，证明了这些标志物对缺血性中风具有出色的预测价值。
本研究阐明了中风发作后3小时至3天内小鼠大脑微环境中中性粒细胞的复杂作用和动态变化。我们已经确定了与缺血性中风中NETs形成相关的关键基因、免疫细胞、信号通路和ceRNA网络。我们的研究构建了一个强大的诊断模型，能够检测缺血性中风的超急性期，AUC值大于0.98。对SN基因F12和PLXDC2进行实验验证，不仅证实了我们模型的预测准确性，还强调了其在临床环境中的潜在效用。这些发现为改善缺血性中风的早期诊断和潜在指导治疗策略提供了有前景的途径。
